--- language: - en library_name: sentence-transformers license: mit pipeline_tag: sentence-similarity tags: - feature-extraction - mteb - sentence-similarity - sentence-transformers - transformers - llama-cpp - gguf-my-repo base_model: avsolatorio/NoInstruct-small-Embedding-v0 model-index: - name: NoInstruct-small-Embedding-v0 results: - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (en) type: mteb/amazon_counterfactual config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 75.76119402985074 - type: ap value: 39.03628777559392 - type: f1 value: 69.85860402259618 - task: type: Classification dataset: name: MTEB AmazonPolarityClassification type: mteb/amazon_polarity config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 93.29920000000001 - type: ap value: 90.03479490717608 - type: f1 value: 93.28554395248467 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (en) type: mteb/amazon_reviews_multi config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 49.98799999999999 - type: f1 value: 49.46151232451642 - task: type: Retrieval dataset: name: MTEB ArguAna type: mteb/arguana config: default split: test revision: c22ab2a51041ffd869aaddef7af8d8215647e41a metrics: - type: map_at_1 value: 31.935000000000002 - type: map_at_10 value: 48.791000000000004 - type: map_at_100 value: 49.619 - type: map_at_1000 value: 49.623 - type: map_at_3 value: 44.334 - type: map_at_5 value: 46.908 - type: mrr_at_1 value: 32.93 - type: mrr_at_10 value: 49.158 - type: mrr_at_100 value: 50.00599999999999 - type: mrr_at_1000 value: 50.01 - type: mrr_at_3 value: 44.618 - type: mrr_at_5 value: 47.325 - type: ndcg_at_1 value: 31.935000000000002 - type: ndcg_at_10 value: 57.593 - type: ndcg_at_100 value: 60.841 - type: ndcg_at_1000 value: 60.924 - type: ndcg_at_3 value: 48.416 - type: ndcg_at_5 value: 53.05 - type: precision_at_1 value: 31.935000000000002 - type: precision_at_10 value: 8.549 - type: precision_at_100 value: 0.9900000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 20.081 - type: precision_at_5 value: 14.296000000000001 - type: recall_at_1 value: 31.935000000000002 - type: recall_at_10 value: 85.491 - type: recall_at_100 value: 99.004 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 60.242 - type: recall_at_5 value: 71.479 - task: type: Clustering dataset: name: MTEB ArxivClusteringP2P type: mteb/arxiv-clustering-p2p config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 47.78438534940855 - task: type: Clustering dataset: name: MTEB ArxivClusteringS2S type: mteb/arxiv-clustering-s2s config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 40.12916178519471 - task: type: Reranking dataset: name: MTEB AskUbuntuDupQuestions type: mteb/askubuntudupquestions-reranking config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 62.125361608299855 - type: mrr value: 74.92525172580574 - task: type: STS dataset: name: MTEB BIOSSES type: mteb/biosses-sts config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 88.64322910336641 - type: cos_sim_spearman value: 87.20138453306345 - type: euclidean_pearson value: 87.08547818178234 - type: euclidean_spearman value: 87.17066094143931 - type: manhattan_pearson value: 87.30053110771618 - type: manhattan_spearman value: 86.86824441211934 - task: type: Classification dataset: name: MTEB Banking77Classification type: mteb/banking77 config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 86.3961038961039 - type: f1 value: 86.3669961645295 - task: type: Clustering dataset: name: MTEB BiorxivClusteringP2P type: mteb/biorxiv-clustering-p2p config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 39.40291404289857 - task: type: Clustering dataset: name: MTEB BiorxivClusteringS2S type: mteb/biorxiv-clustering-s2s config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 35.102356817746816 - task: type: Retrieval dataset: name: MTEB CQADupstackAndroidRetrieval type: mteb/cqadupstack-android config: default split: test revision: f46a197baaae43b4f621051089b82a364682dfeb metrics: - type: map_at_1 value: 31.013 - type: map_at_10 value: 42.681999999999995 - type: map_at_100 value: 44.24 - type: map_at_1000 value: 44.372 - type: map_at_3 value: 39.181 - type: map_at_5 value: 41.071999999999996 - type: mrr_at_1 value: 38.196999999999996 - type: mrr_at_10 value: 48.604 - type: mrr_at_100 value: 49.315 - type: mrr_at_1000 value: 49.363 - type: mrr_at_3 value: 45.756 - type: mrr_at_5 value: 47.43 - type: ndcg_at_1 value: 38.196999999999996 - type: ndcg_at_10 value: 49.344 - type: ndcg_at_100 value: 54.662 - type: ndcg_at_1000 value: 56.665 - type: ndcg_at_3 value: 44.146 - type: ndcg_at_5 value: 46.514 - type: precision_at_1 value: 38.196999999999996 - type: precision_at_10 value: 9.571 - type: precision_at_100 value: 1.542 - type: precision_at_1000 value: 0.202 - type: precision_at_3 value: 21.364 - type: precision_at_5 value: 15.336 - type: recall_at_1 value: 31.013 - type: recall_at_10 value: 61.934999999999995 - type: recall_at_100 value: 83.923 - type: recall_at_1000 value: 96.601 - type: recall_at_3 value: 46.86 - type: recall_at_5 value: 53.620000000000005 - task: type: Retrieval dataset: name: MTEB CQADupstackEnglishRetrieval type: mteb/cqadupstack-english config: default split: test revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 metrics: - type: map_at_1 value: 29.84 - type: map_at_10 value: 39.335 - type: map_at_100 value: 40.647 - type: map_at_1000 value: 40.778 - type: map_at_3 value: 36.556 - type: map_at_5 value: 38.048 - type: mrr_at_1 value: 36.815 - type: mrr_at_10 value: 45.175 - type: mrr_at_100 value: 45.907 - type: mrr_at_1000 value: 45.946999999999996 - type: mrr_at_3 value: 42.909000000000006 - type: mrr_at_5 value: 44.227 - type: ndcg_at_1 value: 36.815 - type: ndcg_at_10 value: 44.783 - type: ndcg_at_100 value: 49.551 - type: ndcg_at_1000 value: 51.612 - type: ndcg_at_3 value: 40.697 - type: ndcg_at_5 value: 42.558 - type: precision_at_1 value: 36.815 - type: precision_at_10 value: 8.363 - type: precision_at_100 value: 1.385 - type: precision_at_1000 value: 0.186 - type: precision_at_3 value: 19.342000000000002 - type: precision_at_5 value: 13.706999999999999 - type: recall_at_1 value: 29.84 - type: recall_at_10 value: 54.164 - type: recall_at_100 value: 74.36 - type: recall_at_1000 value: 87.484 - type: recall_at_3 value: 42.306 - type: recall_at_5 value: 47.371 - task: type: Retrieval dataset: name: MTEB CQADupstackGamingRetrieval type: mteb/cqadupstack-gaming config: default split: test revision: 4885aa143210c98657558c04aaf3dc47cfb54340 metrics: - type: map_at_1 value: 39.231 - type: map_at_10 value: 51.44800000000001 - type: map_at_100 value: 52.574 - type: map_at_1000 value: 52.629999999999995 - type: map_at_3 value: 48.077 - type: map_at_5 value: 50.019000000000005 - type: mrr_at_1 value: 44.89 - type: mrr_at_10 value: 54.803000000000004 - type: mrr_at_100 value: 55.556000000000004 - type: mrr_at_1000 value: 55.584 - type: mrr_at_3 value: 52.32 - type: mrr_at_5 value: 53.846000000000004 - type: ndcg_at_1 value: 44.89 - type: ndcg_at_10 value: 57.228 - type: ndcg_at_100 value: 61.57 - type: ndcg_at_1000 value: 62.613 - type: ndcg_at_3 value: 51.727000000000004 - type: ndcg_at_5 value: 54.496 - type: precision_at_1 value: 44.89 - type: precision_at_10 value: 9.266 - type: precision_at_100 value: 1.2309999999999999 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 23.051 - type: precision_at_5 value: 15.987000000000002 - type: recall_at_1 value: 39.231 - type: recall_at_10 value: 70.82000000000001 - type: recall_at_100 value: 89.446 - type: recall_at_1000 value: 96.665 - type: recall_at_3 value: 56.40500000000001 - type: recall_at_5 value: 62.993 - task: type: Retrieval dataset: name: MTEB CQADupstackGisRetrieval type: mteb/cqadupstack-gis config: default split: test revision: 5003b3064772da1887988e05400cf3806fe491f2 metrics: - type: map_at_1 value: 25.296000000000003 - type: map_at_10 value: 34.021 - type: map_at_100 value: 35.158 - type: map_at_1000 value: 35.233 - type: map_at_3 value: 31.424999999999997 - type: map_at_5 value: 33.046 - type: mrr_at_1 value: 27.232 - type: mrr_at_10 value: 36.103 - type: mrr_at_100 value: 37.076 - type: mrr_at_1000 value: 37.135 - type: mrr_at_3 value: 33.635 - type: mrr_at_5 value: 35.211 - type: ndcg_at_1 value: 27.232 - type: ndcg_at_10 value: 38.878 - type: ndcg_at_100 value: 44.284 - type: ndcg_at_1000 value: 46.268 - type: ndcg_at_3 value: 33.94 - type: ndcg_at_5 value: 36.687 - type: precision_at_1 value: 27.232 - type: precision_at_10 value: 5.921 - type: precision_at_100 value: 0.907 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 14.426 - type: precision_at_5 value: 10.215 - type: recall_at_1 value: 25.296000000000003 - type: recall_at_10 value: 51.708 - type: recall_at_100 value: 76.36699999999999 - type: recall_at_1000 value: 91.306 - type: recall_at_3 value: 38.651 - type: recall_at_5 value: 45.201 - task: type: Retrieval dataset: name: MTEB CQADupstackMathematicaRetrieval type: mteb/cqadupstack-mathematica config: default split: test revision: 90fceea13679c63fe563ded68f3b6f06e50061de metrics: - type: map_at_1 value: 16.24 - type: map_at_10 value: 24.696 - type: map_at_100 value: 25.945 - type: map_at_1000 value: 26.069 - type: map_at_3 value: 22.542 - type: map_at_5 value: 23.526 - type: mrr_at_1 value: 20.149 - type: mrr_at_10 value: 29.584 - type: mrr_at_100 value: 30.548 - type: mrr_at_1000 value: 30.618000000000002 - type: mrr_at_3 value: 27.301 - type: mrr_at_5 value: 28.563 - type: ndcg_at_1 value: 20.149 - type: ndcg_at_10 value: 30.029 - type: ndcg_at_100 value: 35.812 - type: ndcg_at_1000 value: 38.755 - type: ndcg_at_3 value: 26.008 - type: ndcg_at_5 value: 27.517000000000003 - type: precision_at_1 value: 20.149 - type: precision_at_10 value: 5.647 - type: precision_at_100 value: 0.968 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 12.934999999999999 - type: precision_at_5 value: 8.955 - type: recall_at_1 value: 16.24 - type: recall_at_10 value: 41.464 - type: recall_at_100 value: 66.781 - type: recall_at_1000 value: 87.85300000000001 - type: recall_at_3 value: 29.822 - type: recall_at_5 value: 34.096 - task: type: Retrieval dataset: name: MTEB CQADupstackPhysicsRetrieval type: mteb/cqadupstack-physics config: default split: test revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 metrics: - type: map_at_1 value: 29.044999999999998 - type: map_at_10 value: 39.568999999999996 - type: map_at_100 value: 40.831 - type: map_at_1000 value: 40.948 - type: map_at_3 value: 36.495 - type: map_at_5 value: 38.21 - type: mrr_at_1 value: 35.611 - type: mrr_at_10 value: 45.175 - type: mrr_at_100 value: 45.974 - type: mrr_at_1000 value: 46.025 - type: mrr_at_3 value: 42.765 - type: mrr_at_5 value: 44.151 - type: ndcg_at_1 value: 35.611 - type: ndcg_at_10 value: 45.556999999999995 - type: ndcg_at_100 value: 50.86000000000001 - type: ndcg_at_1000 value: 52.983000000000004 - type: ndcg_at_3 value: 40.881 - type: ndcg_at_5 value: 43.035000000000004 - type: precision_at_1 value: 35.611 - type: precision_at_10 value: 8.306 - type: precision_at_100 value: 1.276 - type: precision_at_1000 value: 0.165 - type: precision_at_3 value: 19.57 - type: precision_at_5 value: 13.725000000000001 - type: recall_at_1 value: 29.044999999999998 - type: recall_at_10 value: 57.513999999999996 - type: recall_at_100 value: 80.152 - type: recall_at_1000 value: 93.982 - type: recall_at_3 value: 44.121 - type: recall_at_5 value: 50.007000000000005 - task: type: Retrieval dataset: name: MTEB CQADupstackProgrammersRetrieval type: mteb/cqadupstack-programmers config: default split: test revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 metrics: - type: map_at_1 value: 22.349 - type: map_at_10 value: 33.434000000000005 - type: map_at_100 value: 34.8 - type: map_at_1000 value: 34.919 - type: map_at_3 value: 30.348000000000003 - type: map_at_5 value: 31.917 - type: mrr_at_1 value: 28.195999999999998 - type: mrr_at_10 value: 38.557 - type: mrr_at_100 value: 39.550999999999995 - type: mrr_at_1000 value: 39.607 - type: mrr_at_3 value: 36.035000000000004 - type: mrr_at_5 value: 37.364999999999995 - type: ndcg_at_1 value: 28.195999999999998 - type: ndcg_at_10 value: 39.656000000000006 - type: ndcg_at_100 value: 45.507999999999996 - type: ndcg_at_1000 value: 47.848 - type: ndcg_at_3 value: 34.609 - type: ndcg_at_5 value: 36.65 - type: precision_at_1 value: 28.195999999999998 - type: precision_at_10 value: 7.534000000000001 - type: precision_at_100 value: 1.217 - type: precision_at_1000 value: 0.158 - type: precision_at_3 value: 17.085 - type: precision_at_5 value: 12.169 - type: recall_at_1 value: 22.349 - type: recall_at_10 value: 53.127 - type: recall_at_100 value: 77.884 - type: recall_at_1000 value: 93.705 - type: recall_at_3 value: 38.611000000000004 - type: recall_at_5 value: 44.182 - task: type: Retrieval dataset: name: MTEB CQADupstackRetrieval type: mteb/cqadupstack config: default split: test revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 metrics: - type: map_at_1 value: 25.215749999999996 - type: map_at_10 value: 34.332750000000004 - type: map_at_100 value: 35.58683333333333 - type: map_at_1000 value: 35.70458333333333 - type: map_at_3 value: 31.55441666666667 - type: map_at_5 value: 33.100833333333334 - type: mrr_at_1 value: 29.697250000000004 - type: mrr_at_10 value: 38.372249999999994 - type: mrr_at_100 value: 39.26708333333334 - type: mrr_at_1000 value: 39.3265 - type: mrr_at_3 value: 35.946083333333334 - type: mrr_at_5 value: 37.336999999999996 - type: ndcg_at_1 value: 29.697250000000004 - type: ndcg_at_10 value: 39.64575 - type: ndcg_at_100 value: 44.996833333333335 - type: ndcg_at_1000 value: 47.314499999999995 - type: ndcg_at_3 value: 34.93383333333334 - type: ndcg_at_5 value: 37.15291666666667 - type: precision_at_1 value: 29.697250000000004 - type: precision_at_10 value: 6.98825 - type: precision_at_100 value: 1.138 - type: precision_at_1000 value: 0.15283333333333332 - type: precision_at_3 value: 16.115583333333333 - type: precision_at_5 value: 11.460916666666666 - type: recall_at_1 value: 25.215749999999996 - type: recall_at_10 value: 51.261250000000004 - type: recall_at_100 value: 74.67258333333334 - type: recall_at_1000 value: 90.72033333333334 - type: recall_at_3 value: 38.1795 - type: recall_at_5 value: 43.90658333333334 - task: type: Retrieval dataset: name: MTEB CQADupstackStatsRetrieval type: mteb/cqadupstack-stats config: default split: test revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a metrics: - type: map_at_1 value: 24.352 - type: map_at_10 value: 30.576999999999998 - type: map_at_100 value: 31.545 - type: map_at_1000 value: 31.642 - type: map_at_3 value: 28.605000000000004 - type: map_at_5 value: 29.828 - type: mrr_at_1 value: 26.994 - type: mrr_at_10 value: 33.151 - type: mrr_at_100 value: 33.973 - type: mrr_at_1000 value: 34.044999999999995 - type: mrr_at_3 value: 31.135 - type: mrr_at_5 value: 32.262 - type: ndcg_at_1 value: 26.994 - type: ndcg_at_10 value: 34.307 - type: ndcg_at_100 value: 39.079 - type: ndcg_at_1000 value: 41.548 - type: ndcg_at_3 value: 30.581000000000003 - type: ndcg_at_5 value: 32.541 - type: precision_at_1 value: 26.994 - type: precision_at_10 value: 5.244999999999999 - type: precision_at_100 value: 0.831 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 12.781 - type: precision_at_5 value: 9.017999999999999 - type: recall_at_1 value: 24.352 - type: recall_at_10 value: 43.126999999999995 - type: recall_at_100 value: 64.845 - type: recall_at_1000 value: 83.244 - type: recall_at_3 value: 33.308 - type: recall_at_5 value: 37.984 - task: type: Retrieval dataset: name: MTEB CQADupstackTexRetrieval type: mteb/cqadupstack-tex config: default split: test revision: 46989137a86843e03a6195de44b09deda022eec7 metrics: - type: map_at_1 value: 16.592000000000002 - type: map_at_10 value: 23.29 - type: map_at_100 value: 24.423000000000002 - type: map_at_1000 value: 24.554000000000002 - type: map_at_3 value: 20.958 - type: map_at_5 value: 22.267 - type: mrr_at_1 value: 20.061999999999998 - type: mrr_at_10 value: 26.973999999999997 - type: mrr_at_100 value: 27.944999999999997 - type: mrr_at_1000 value: 28.023999999999997 - type: mrr_at_3 value: 24.839 - type: mrr_at_5 value: 26.033 - type: ndcg_at_1 value: 20.061999999999998 - type: ndcg_at_10 value: 27.682000000000002 - type: ndcg_at_100 value: 33.196 - type: ndcg_at_1000 value: 36.246 - type: ndcg_at_3 value: 23.559 - type: ndcg_at_5 value: 25.507 - type: precision_at_1 value: 20.061999999999998 - type: precision_at_10 value: 5.086 - type: precision_at_100 value: 0.9249999999999999 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 11.046 - type: precision_at_5 value: 8.149000000000001 - type: recall_at_1 value: 16.592000000000002 - type: recall_at_10 value: 37.181999999999995 - type: recall_at_100 value: 62.224999999999994 - type: recall_at_1000 value: 84.072 - type: recall_at_3 value: 25.776 - type: recall_at_5 value: 30.680000000000003 - task: type: Retrieval dataset: name: MTEB CQADupstackUnixRetrieval type: mteb/cqadupstack-unix config: default split: test revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 metrics: - type: map_at_1 value: 26.035999999999998 - type: map_at_10 value: 34.447 - type: map_at_100 value: 35.697 - type: map_at_1000 value: 35.802 - type: map_at_3 value: 31.64 - type: map_at_5 value: 33.056999999999995 - type: mrr_at_1 value: 29.851 - type: mrr_at_10 value: 38.143 - type: mrr_at_100 value: 39.113 - type: mrr_at_1000 value: 39.175 - type: mrr_at_3 value: 35.665 - type: mrr_at_5 value: 36.901 - type: ndcg_at_1 value: 29.851 - type: ndcg_at_10 value: 39.554 - type: ndcg_at_100 value: 45.091 - type: ndcg_at_1000 value: 47.504000000000005 - type: ndcg_at_3 value: 34.414 - type: ndcg_at_5 value: 36.508 - type: precision_at_1 value: 29.851 - type: precision_at_10 value: 6.614000000000001 - type: precision_at_100 value: 1.051 - type: precision_at_1000 value: 0.13699999999999998 - type: precision_at_3 value: 15.329999999999998 - type: precision_at_5 value: 10.671999999999999 - type: recall_at_1 value: 26.035999999999998 - type: recall_at_10 value: 51.396 - type: recall_at_100 value: 75.09 - type: recall_at_1000 value: 91.904 - type: recall_at_3 value: 37.378 - type: recall_at_5 value: 42.69 - task: type: Retrieval dataset: name: MTEB CQADupstackWebmastersRetrieval type: mteb/cqadupstack-webmasters config: default split: test revision: 160c094312a0e1facb97e55eeddb698c0abe3571 metrics: - type: map_at_1 value: 23.211000000000002 - type: map_at_10 value: 32.231 - type: map_at_100 value: 33.772999999999996 - type: map_at_1000 value: 33.982 - type: map_at_3 value: 29.128 - type: map_at_5 value: 31.002999999999997 - type: mrr_at_1 value: 27.668 - type: mrr_at_10 value: 36.388 - type: mrr_at_100 value: 37.384 - type: mrr_at_1000 value: 37.44 - type: mrr_at_3 value: 33.762 - type: mrr_at_5 value: 35.234 - type: ndcg_at_1 value: 27.668 - type: ndcg_at_10 value: 38.043 - type: ndcg_at_100 value: 44.21 - type: ndcg_at_1000 value: 46.748 - type: ndcg_at_3 value: 32.981 - type: ndcg_at_5 value: 35.58 - type: precision_at_1 value: 27.668 - type: precision_at_10 value: 7.352 - type: precision_at_100 value: 1.5 - type: precision_at_1000 value: 0.23700000000000002 - type: precision_at_3 value: 15.613 - type: precision_at_5 value: 11.501999999999999 - type: recall_at_1 value: 23.211000000000002 - type: recall_at_10 value: 49.851 - type: recall_at_100 value: 77.596 - type: recall_at_1000 value: 93.683 - type: recall_at_3 value: 35.403 - type: recall_at_5 value: 42.485 - task: type: Retrieval dataset: name: MTEB CQADupstackWordpressRetrieval type: mteb/cqadupstack-wordpress config: default split: test revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 metrics: - type: map_at_1 value: 19.384 - type: map_at_10 value: 26.262999999999998 - type: map_at_100 value: 27.409 - type: map_at_1000 value: 27.526 - type: map_at_3 value: 23.698 - type: map_at_5 value: 25.217 - type: mrr_at_1 value: 20.702 - type: mrr_at_10 value: 27.810000000000002 - type: mrr_at_100 value: 28.863 - type: mrr_at_1000 value: 28.955 - type: mrr_at_3 value: 25.230999999999998 - type: mrr_at_5 value: 26.821 - type: ndcg_at_1 value: 20.702 - type: ndcg_at_10 value: 30.688 - type: ndcg_at_100 value: 36.138999999999996 - type: ndcg_at_1000 value: 38.984 - type: ndcg_at_3 value: 25.663000000000004 - type: ndcg_at_5 value: 28.242 - type: precision_at_1 value: 20.702 - type: precision_at_10 value: 4.954 - type: precision_at_100 value: 0.823 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 10.844 - type: precision_at_5 value: 8.096 - type: recall_at_1 value: 19.384 - type: recall_at_10 value: 42.847 - type: recall_at_100 value: 67.402 - type: recall_at_1000 value: 88.145 - type: recall_at_3 value: 29.513 - type: recall_at_5 value: 35.57 - task: type: Retrieval dataset: name: MTEB ClimateFEVER type: mteb/climate-fever config: default split: test revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 metrics: - type: map_at_1 value: 14.915000000000001 - type: map_at_10 value: 25.846999999999998 - type: map_at_100 value: 27.741 - type: map_at_1000 value: 27.921000000000003 - type: map_at_3 value: 21.718 - type: map_at_5 value: 23.948 - type: mrr_at_1 value: 33.941 - type: mrr_at_10 value: 46.897 - type: mrr_at_100 value: 47.63 - type: mrr_at_1000 value: 47.658 - type: mrr_at_3 value: 43.919999999999995 - type: mrr_at_5 value: 45.783 - type: ndcg_at_1 value: 33.941 - type: ndcg_at_10 value: 35.202 - type: ndcg_at_100 value: 42.132 - type: ndcg_at_1000 value: 45.190999999999995 - type: ndcg_at_3 value: 29.68 - type: ndcg_at_5 value: 31.631999999999998 - type: precision_at_1 value: 33.941 - type: precision_at_10 value: 10.906 - type: precision_at_100 value: 1.8339999999999999 - type: precision_at_1000 value: 0.241 - type: precision_at_3 value: 22.606 - type: precision_at_5 value: 17.081 - type: recall_at_1 value: 14.915000000000001 - type: recall_at_10 value: 40.737 - type: recall_at_100 value: 64.42 - type: recall_at_1000 value: 81.435 - type: recall_at_3 value: 26.767000000000003 - type: recall_at_5 value: 32.895 - task: type: Retrieval dataset: name: MTEB DBPedia type: mteb/dbpedia config: default split: test revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 metrics: - type: map_at_1 value: 8.665000000000001 - type: map_at_10 value: 19.087 - type: map_at_100 value: 26.555 - type: map_at_1000 value: 28.105999999999998 - type: map_at_3 value: 13.858999999999998 - type: map_at_5 value: 16.083 - type: mrr_at_1 value: 68.5 - type: mrr_at_10 value: 76.725 - type: mrr_at_100 value: 76.974 - type: mrr_at_1000 value: 76.981 - type: mrr_at_3 value: 75.583 - type: mrr_at_5 value: 76.208 - type: ndcg_at_1 value: 55.875 - type: ndcg_at_10 value: 41.018 - type: ndcg_at_100 value: 44.982 - type: ndcg_at_1000 value: 52.43 - type: ndcg_at_3 value: 46.534 - type: ndcg_at_5 value: 43.083 - type: precision_at_1 value: 68.5 - type: precision_at_10 value: 32.35 - type: precision_at_100 value: 10.078 - type: precision_at_1000 value: 1.957 - type: precision_at_3 value: 50.083 - type: precision_at_5 value: 41.3 - type: recall_at_1 value: 8.665000000000001 - type: recall_at_10 value: 24.596999999999998 - type: recall_at_100 value: 50.612 - type: recall_at_1000 value: 74.24 - type: recall_at_3 value: 15.337 - type: recall_at_5 value: 18.796 - task: type: Classification dataset: name: MTEB EmotionClassification type: mteb/emotion config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 55.06500000000001 - type: f1 value: 49.827367590822035 - task: type: Retrieval dataset: name: MTEB FEVER type: mteb/fever config: default split: test revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 metrics: - type: map_at_1 value: 76.059 - type: map_at_10 value: 83.625 - type: map_at_100 value: 83.845 - type: map_at_1000 value: 83.858 - type: map_at_3 value: 82.67099999999999 - type: map_at_5 value: 83.223 - type: mrr_at_1 value: 82.013 - type: mrr_at_10 value: 88.44800000000001 - type: mrr_at_100 value: 88.535 - type: mrr_at_1000 value: 88.537 - type: mrr_at_3 value: 87.854 - type: mrr_at_5 value: 88.221 - type: ndcg_at_1 value: 82.013 - type: ndcg_at_10 value: 87.128 - type: ndcg_at_100 value: 87.922 - type: ndcg_at_1000 value: 88.166 - type: ndcg_at_3 value: 85.648 - type: ndcg_at_5 value: 86.366 - type: precision_at_1 value: 82.013 - type: precision_at_10 value: 10.32 - type: precision_at_100 value: 1.093 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 32.408 - type: precision_at_5 value: 19.973 - type: recall_at_1 value: 76.059 - type: recall_at_10 value: 93.229 - type: recall_at_100 value: 96.387 - type: recall_at_1000 value: 97.916 - type: recall_at_3 value: 89.025 - type: recall_at_5 value: 90.96300000000001 - task: type: Retrieval dataset: name: MTEB FiQA2018 type: mteb/fiqa config: default split: test revision: 27a168819829fe9bcd655c2df245fb19452e8e06 metrics: - type: map_at_1 value: 20.479 - type: map_at_10 value: 33.109 - type: map_at_100 value: 34.803 - type: map_at_1000 value: 35.003 - type: map_at_3 value: 28.967 - type: map_at_5 value: 31.385 - type: mrr_at_1 value: 40.278000000000006 - type: mrr_at_10 value: 48.929 - type: mrr_at_100 value: 49.655 - type: mrr_at_1000 value: 49.691 - type: mrr_at_3 value: 46.605000000000004 - type: mrr_at_5 value: 48.056 - type: ndcg_at_1 value: 40.278000000000006 - type: ndcg_at_10 value: 40.649 - type: ndcg_at_100 value: 47.027 - type: ndcg_at_1000 value: 50.249 - type: ndcg_at_3 value: 37.364000000000004 - type: ndcg_at_5 value: 38.494 - type: precision_at_1 value: 40.278000000000006 - type: precision_at_10 value: 11.327 - type: precision_at_100 value: 1.802 - type: precision_at_1000 value: 0.23700000000000002 - type: precision_at_3 value: 25.102999999999998 - type: precision_at_5 value: 18.457 - type: recall_at_1 value: 20.479 - type: recall_at_10 value: 46.594 - type: recall_at_100 value: 71.101 - type: recall_at_1000 value: 90.31099999999999 - type: recall_at_3 value: 33.378 - type: recall_at_5 value: 39.587 - task: type: Retrieval dataset: name: MTEB HotpotQA type: mteb/hotpotqa config: default split: test revision: ab518f4d6fcca38d87c25209f94beba119d02014 metrics: - type: map_at_1 value: 36.59 - type: map_at_10 value: 58.178 - type: map_at_100 value: 59.095 - type: map_at_1000 value: 59.16400000000001 - type: map_at_3 value: 54.907 - type: map_at_5 value: 56.89999999999999 - type: mrr_at_1 value: 73.18 - type: mrr_at_10 value: 79.935 - type: mrr_at_100 value: 80.16799999999999 - type: mrr_at_1000 value: 80.17800000000001 - type: mrr_at_3 value: 78.776 - type: mrr_at_5 value: 79.522 - type: ndcg_at_1 value: 73.18 - type: ndcg_at_10 value: 66.538 - type: ndcg_at_100 value: 69.78 - type: ndcg_at_1000 value: 71.102 - type: ndcg_at_3 value: 61.739 - type: ndcg_at_5 value: 64.35600000000001 - type: precision_at_1 value: 73.18 - type: precision_at_10 value: 14.035 - type: precision_at_100 value: 1.657 - type: precision_at_1000 value: 0.183 - type: precision_at_3 value: 39.684999999999995 - type: precision_at_5 value: 25.885 - type: recall_at_1 value: 36.59 - type: recall_at_10 value: 70.176 - type: recall_at_100 value: 82.836 - type: recall_at_1000 value: 91.526 - type: recall_at_3 value: 59.526999999999994 - type: recall_at_5 value: 64.713 - task: type: Classification dataset: name: MTEB ImdbClassification type: mteb/imdb config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 90.1472 - type: ap value: 85.73994227076815 - type: f1 value: 90.1271700788608 - task: type: Retrieval dataset: name: MTEB MSMARCO type: mteb/msmarco config: default split: dev revision: c5a29a104738b98a9e76336939199e264163d4a0 metrics: - type: map_at_1 value: 21.689 - type: map_at_10 value: 33.518 - type: map_at_100 value: 34.715 - type: map_at_1000 value: 34.766000000000005 - type: map_at_3 value: 29.781000000000002 - type: map_at_5 value: 31.838 - type: mrr_at_1 value: 22.249 - type: mrr_at_10 value: 34.085 - type: mrr_at_100 value: 35.223 - type: mrr_at_1000 value: 35.266999999999996 - type: mrr_at_3 value: 30.398999999999997 - type: mrr_at_5 value: 32.437 - type: ndcg_at_1 value: 22.249 - type: ndcg_at_10 value: 40.227000000000004 - type: ndcg_at_100 value: 45.961999999999996 - type: ndcg_at_1000 value: 47.248000000000005 - type: ndcg_at_3 value: 32.566 - type: ndcg_at_5 value: 36.229 - type: precision_at_1 value: 22.249 - type: precision_at_10 value: 6.358 - type: precision_at_100 value: 0.923 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 13.83 - type: precision_at_5 value: 10.145999999999999 - type: recall_at_1 value: 21.689 - type: recall_at_10 value: 60.92999999999999 - type: recall_at_100 value: 87.40599999999999 - type: recall_at_1000 value: 97.283 - type: recall_at_3 value: 40.01 - type: recall_at_5 value: 48.776 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (en) type: mteb/mtop_domain config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 95.28727770177838 - type: f1 value: 95.02577308660041 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (en) type: mteb/mtop_intent config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 79.5736434108527 - type: f1 value: 61.2451202054398 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (en) type: mteb/amazon_massive_intent config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 76.01210490921318 - type: f1 value: 73.70188053982473 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (en) type: mteb/amazon_massive_scenario config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 79.33422999327504 - type: f1 value: 79.48369022509658 - task: type: Clustering dataset: name: MTEB MedrxivClusteringP2P type: mteb/medrxiv-clustering-p2p config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 34.70891567267726 - task: type: Clustering dataset: name: MTEB MedrxivClusteringS2S type: mteb/medrxiv-clustering-s2s config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 32.15203494451706 - task: type: Reranking dataset: name: MTEB MindSmallReranking type: mteb/mind_small config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 31.919517862194173 - type: mrr value: 33.15466289140483 - task: type: Retrieval dataset: name: MTEB NFCorpus type: mteb/nfcorpus config: default split: test revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 metrics: - type: map_at_1 value: 5.992 - type: map_at_10 value: 13.197000000000001 - type: map_at_100 value: 16.907 - type: map_at_1000 value: 18.44 - type: map_at_3 value: 9.631 - type: map_at_5 value: 11.243 - type: mrr_at_1 value: 44.272 - type: mrr_at_10 value: 53.321 - type: mrr_at_100 value: 53.903 - type: mrr_at_1000 value: 53.952999999999996 - type: mrr_at_3 value: 51.393 - type: mrr_at_5 value: 52.708999999999996 - type: ndcg_at_1 value: 42.415000000000006 - type: ndcg_at_10 value: 34.921 - type: ndcg_at_100 value: 32.384 - type: ndcg_at_1000 value: 41.260000000000005 - type: ndcg_at_3 value: 40.186 - type: ndcg_at_5 value: 37.89 - type: precision_at_1 value: 44.272 - type: precision_at_10 value: 26.006 - type: precision_at_100 value: 8.44 - type: precision_at_1000 value: 2.136 - type: precision_at_3 value: 37.977 - type: precision_at_5 value: 32.755 - type: recall_at_1 value: 5.992 - type: recall_at_10 value: 17.01 - type: recall_at_100 value: 33.080999999999996 - type: recall_at_1000 value: 65.054 - type: recall_at_3 value: 10.528 - type: recall_at_5 value: 13.233 - task: type: Retrieval dataset: name: MTEB NQ type: mteb/nq config: default split: test revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 metrics: - type: map_at_1 value: 28.871999999999996 - type: map_at_10 value: 43.286 - type: map_at_100 value: 44.432 - type: map_at_1000 value: 44.464999999999996 - type: map_at_3 value: 38.856 - type: map_at_5 value: 41.514 - type: mrr_at_1 value: 32.619 - type: mrr_at_10 value: 45.75 - type: mrr_at_100 value: 46.622 - type: mrr_at_1000 value: 46.646 - type: mrr_at_3 value: 41.985 - type: mrr_at_5 value: 44.277 - type: ndcg_at_1 value: 32.59 - type: ndcg_at_10 value: 50.895999999999994 - type: ndcg_at_100 value: 55.711999999999996 - type: ndcg_at_1000 value: 56.48800000000001 - type: ndcg_at_3 value: 42.504999999999995 - type: ndcg_at_5 value: 46.969 - type: precision_at_1 value: 32.59 - type: precision_at_10 value: 8.543000000000001 - type: precision_at_100 value: 1.123 - type: precision_at_1000 value: 0.12 - type: precision_at_3 value: 19.448 - type: precision_at_5 value: 14.218 - type: recall_at_1 value: 28.871999999999996 - type: recall_at_10 value: 71.748 - type: recall_at_100 value: 92.55499999999999 - type: recall_at_1000 value: 98.327 - type: recall_at_3 value: 49.944 - type: recall_at_5 value: 60.291 - task: type: Retrieval dataset: name: MTEB QuoraRetrieval type: mteb/quora config: default split: test revision: e4e08e0b7dbe3c8700f0daef558ff32256715259 metrics: - type: map_at_1 value: 70.664 - type: map_at_10 value: 84.681 - type: map_at_100 value: 85.289 - type: map_at_1000 value: 85.306 - type: map_at_3 value: 81.719 - type: map_at_5 value: 83.601 - type: mrr_at_1 value: 81.35 - type: mrr_at_10 value: 87.591 - type: mrr_at_100 value: 87.691 - type: mrr_at_1000 value: 87.693 - type: mrr_at_3 value: 86.675 - type: mrr_at_5 value: 87.29299999999999 - type: ndcg_at_1 value: 81.33 - type: ndcg_at_10 value: 88.411 - type: ndcg_at_100 value: 89.579 - type: ndcg_at_1000 value: 89.687 - type: ndcg_at_3 value: 85.613 - type: ndcg_at_5 value: 87.17 - type: precision_at_1 value: 81.33 - type: precision_at_10 value: 13.422 - type: precision_at_100 value: 1.5270000000000001 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 37.463 - type: precision_at_5 value: 24.646 - type: recall_at_1 value: 70.664 - type: recall_at_10 value: 95.54 - type: recall_at_100 value: 99.496 - type: recall_at_1000 value: 99.978 - type: recall_at_3 value: 87.481 - type: recall_at_5 value: 91.88499999999999 - task: type: Clustering dataset: name: MTEB RedditClustering type: mteb/reddit-clustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 55.40341814991112 - task: type: Clustering dataset: name: MTEB RedditClusteringP2P type: mteb/reddit-clustering-p2p config: default split: test revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 metrics: - type: v_measure value: 61.231318481346655 - task: type: Retrieval dataset: name: MTEB SCIDOCS type: mteb/scidocs config: default split: test revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88 metrics: - type: map_at_1 value: 4.833 - type: map_at_10 value: 13.149 - type: map_at_100 value: 15.578 - type: map_at_1000 value: 15.963 - type: map_at_3 value: 9.269 - type: map_at_5 value: 11.182 - type: mrr_at_1 value: 23.9 - type: mrr_at_10 value: 35.978 - type: mrr_at_100 value: 37.076 - type: mrr_at_1000 value: 37.126 - type: mrr_at_3 value: 32.333 - type: mrr_at_5 value: 34.413 - type: ndcg_at_1 value: 23.9 - type: ndcg_at_10 value: 21.823 - type: ndcg_at_100 value: 30.833 - type: ndcg_at_1000 value: 36.991 - type: ndcg_at_3 value: 20.465 - type: ndcg_at_5 value: 17.965999999999998 - type: precision_at_1 value: 23.9 - type: precision_at_10 value: 11.49 - type: precision_at_100 value: 2.444 - type: precision_at_1000 value: 0.392 - type: precision_at_3 value: 19.3 - type: precision_at_5 value: 15.959999999999999 - type: recall_at_1 value: 4.833 - type: recall_at_10 value: 23.294999999999998 - type: recall_at_100 value: 49.63 - type: recall_at_1000 value: 79.49199999999999 - type: recall_at_3 value: 11.732 - type: recall_at_5 value: 16.167 - task: type: STS dataset: name: MTEB SICK-R type: mteb/sickr-sts config: default split: test revision: 20a6d6f312dd54037fe07a32d58e5e168867909d metrics: - type: cos_sim_pearson value: 85.62938108735759 - type: cos_sim_spearman value: 80.30777094408789 - type: euclidean_pearson value: 82.94516686659536 - type: euclidean_spearman value: 80.34489663248169 - type: manhattan_pearson value: 82.85830094736245 - type: manhattan_spearman value: 80.24902623215449 - task: type: STS dataset: name: MTEB STS12 type: mteb/sts12-sts config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - 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task: type: Clustering dataset: name: MTEB StackExchangeClustering type: mteb/stackexchange-clustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 62.045718843534736 - task: type: Clustering dataset: name: MTEB StackExchangeClusteringP2P type: mteb/stackexchange-clustering-p2p config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 36.6501777041092 - task: type: Reranking dataset: name: MTEB StackOverflowDupQuestions type: mteb/stackoverflowdupquestions-reranking config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 52.963913408053955 - type: mrr value: 53.87972423818012 - task: type: Summarization dataset: name: MTEB SummEval type: mteb/summeval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.44195730764998 - type: cos_sim_spearman value: 30.59626288679397 - 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type: precision_at_3 value: 87.333 - type: precision_at_5 value: 85.2 - type: recall_at_1 value: 0.24 - type: recall_at_10 value: 2.205 - type: recall_at_100 value: 15.068000000000001 - type: recall_at_1000 value: 51.796 - type: recall_at_3 value: 0.698 - type: recall_at_5 value: 1.1199999999999999 - task: type: Retrieval dataset: name: MTEB Touche2020 type: mteb/touche2020 config: default split: test revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f metrics: - type: map_at_1 value: 3.066 - type: map_at_10 value: 9.219 - type: map_at_100 value: 15.387 - type: map_at_1000 value: 16.957 - type: map_at_3 value: 5.146 - type: map_at_5 value: 6.6739999999999995 - type: mrr_at_1 value: 40.816 - type: mrr_at_10 value: 50.844 - type: mrr_at_100 value: 51.664 - type: mrr_at_1000 value: 51.664 - type: mrr_at_3 value: 46.259 - type: mrr_at_5 value: 49.116 - type: ndcg_at_1 value: 37.755 - type: ndcg_at_10 value: 23.477 - type: ndcg_at_100 value: 36.268 - type: ndcg_at_1000 value: 47.946 - type: ndcg_at_3 value: 25.832 - type: ndcg_at_5 value: 24.235 - type: precision_at_1 value: 40.816 - type: precision_at_10 value: 20.204 - type: precision_at_100 value: 7.611999999999999 - type: precision_at_1000 value: 1.543 - type: precision_at_3 value: 25.169999999999998 - type: precision_at_5 value: 23.265 - type: recall_at_1 value: 3.066 - type: recall_at_10 value: 14.985999999999999 - type: recall_at_100 value: 47.902 - type: recall_at_1000 value: 83.56400000000001 - type: recall_at_3 value: 5.755 - type: recall_at_5 value: 8.741999999999999 - task: type: Classification dataset: name: MTEB ToxicConversationsClassification type: mteb/toxic_conversations_50k config: default split: test revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de metrics: - type: accuracy value: 69.437 - type: ap value: 12.844066827082706 - type: f1 value: 52.74974809872495 - task: type: Classification dataset: name: MTEB TweetSentimentExtractionClassification type: mteb/tweet_sentiment_extraction config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 61.26768534238823 - type: f1 value: 61.65100187399282 - task: type: Clustering dataset: name: MTEB TwentyNewsgroupsClustering type: mteb/twentynewsgroups-clustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 49.860968711078804 - task: type: PairClassification dataset: name: MTEB TwitterSemEval2015 type: mteb/twittersemeval2015-pairclassification config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 85.7423854085951 - type: cos_sim_ap value: 73.47560303339571 - type: cos_sim_f1 value: 67.372778183589 - type: cos_sim_precision value: 62.54520795660036 - type: cos_sim_recall value: 73.00791556728232 - type: dot_accuracy value: 85.36091077069798 - type: dot_ap value: 72.42521572307255 - type: dot_f1 value: 66.90576304724215 - type: dot_precision value: 62.96554934823091 - type: dot_recall value: 71.37203166226914 - type: euclidean_accuracy value: 85.76026703224653 - type: euclidean_ap value: 73.44852563860128 - type: euclidean_f1 value: 67.3 - type: euclidean_precision value: 63.94299287410926 - type: euclidean_recall value: 71.02902374670185 - type: manhattan_accuracy value: 85.7423854085951 - type: manhattan_ap value: 73.2635034755551 - type: manhattan_f1 value: 67.3180263800684 - type: manhattan_precision value: 62.66484765802638 - type: manhattan_recall value: 72.71767810026385 - type: max_accuracy value: 85.76026703224653 - type: max_ap value: 73.47560303339571 - type: max_f1 value: 67.372778183589 - task: type: PairClassification dataset: name: MTEB TwitterURLCorpus type: mteb/twitterurlcorpus-pairclassification config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.67543757519307 - type: cos_sim_ap value: 85.35516518531304 - type: cos_sim_f1 value: 77.58197635511934 - type: cos_sim_precision value: 75.01078360891445 - type: cos_sim_recall value: 80.33569448721897 - type: dot_accuracy value: 87.61400240617844 - type: dot_ap value: 83.0774968268665 - type: dot_f1 value: 75.68229012162561 - type: dot_precision value: 72.99713876967095 - type: dot_recall value: 78.57252848783493 - type: euclidean_accuracy value: 88.73753250281368 - type: euclidean_ap value: 85.48043564821317 - type: euclidean_f1 value: 77.75975862719216 - type: euclidean_precision value: 76.21054187920456 - type: euclidean_recall value: 79.37326763166 - type: manhattan_accuracy value: 88.75111576823068 - type: manhattan_ap value: 85.44993439423668 - type: manhattan_f1 value: 77.6861329994845 - type: manhattan_precision value: 74.44601270289344 - type: manhattan_recall value: 81.22112719433323 - type: max_accuracy value: 88.75111576823068 - type: max_ap value: 85.48043564821317 - type: max_f1 value: 77.75975862719216 --- # twine-network/NoInstruct-small-Embedding-v0-Q8_0-GGUF This model was converted to GGUF format from [`avsolatorio/NoInstruct-small-Embedding-v0`](https://huggingface.co/avsolatorio/NoInstruct-small-Embedding-v0) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/avsolatorio/NoInstruct-small-Embedding-v0) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo twine-network/NoInstruct-small-Embedding-v0-Q8_0-GGUF --hf-file noinstruct-small-embedding-v0-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo twine-network/NoInstruct-small-Embedding-v0-Q8_0-GGUF --hf-file noinstruct-small-embedding-v0-q8_0.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo twine-network/NoInstruct-small-Embedding-v0-Q8_0-GGUF --hf-file noinstruct-small-embedding-v0-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo twine-network/NoInstruct-small-Embedding-v0-Q8_0-GGUF --hf-file noinstruct-small-embedding-v0-q8_0.gguf -c 2048 ```